Lifetime Metabolomics for Paediatric Liver Cancer Detection and Therapy Assessment Using Organ-on-Chip Platforms

Projektbeschreibung

Plattform für personalisierte Krankheitsmetabolomik von der Diagnose bis zur Behandlung

Im Körper werden beim Abbau und Aufbau von Molekülen fortlaufend unzählige kleine Moleküle namens Metaboliten gebildet. Metaboliten sind wichtige Marker für Gesundheit und Krankheit. Derzeit sind die Ansätze zur Erforschung der Metabolomik – der weitreichenden Untersuchung von Metaboliten – innerhalb und zwischen Zellen bei Krebs für die personalisierte Medizin begrenzt. Aus dem ERC-finanzierten Projekt LIFETIME soll eine Organ-auf-Chip-Plattform hervorgehen, mit der ein metabolomischer Fingerabdruck einer Krankheit vom Ausbruch bis zu Behandlung in vivo aufgezeichnet werden kann. Mit Hepatoblastomen als Entwicklungsmodell wird die Plattform gleichzeitige, wiederholbare Messungen über Zeit ermöglichen, um Details über die Tumorphänotypen und die Mikroumgebung im Laufe der Zeit aufzudecken. So können neue Biomarker entdeckt werden.

Ziel

"Understanding cancer metabolism at the individual patient level is central to making accurate early-stage diagnoses and providing effective patient-specific treatments. While some methods do exist to study intra-cell metabolomics and inter-cell metabolic flux alterations (e.g. PET, MRI), their scalability and sensitivity is limited, hindering reliable investigations long-term.
LIFETIME aims to develop a single platform for ""lifetime metabolomics"", where the metabolic fingerprint of a disease is traced throughout patient onset in vivo, analysis ex vivo, and through to treatment. Technologically this involves rapid metabolomic profiling of the cancer model, using microfluidic 3D-cell-cultures in organ-on-chip (OoC) structures and magnetic resonance spectroscopic imaging (MRSI). Scientifically, the disease-specific case study chosen is hepatoblastoma (HB), the most common liver cancer in children, where the platform could improve patient survival rate and quality of life. Metabolic contrast in three phenotypes of HB mouse models (intrahepatic, intravenous, subcutaneous) and their OoC counterparts will be assessed.
A unique benefit of the platform will be its capability for parallel, repeatable measurements on samples to track therapeutic-induced metabolic alterations over time. This will unveil tumours' detailed molecular phenotypes and shed light on their correlation with tumour heterogeneity and interactions within tumour microenvironment.
Overall, LIFETIME will enable the definition of new reliable biomarkers of HB that propel the development of targeted therapies. If successful, the scalability of the platform will hold the important ability to bridge in vivo and in vitro assessment, from biopsy-derived cell cultures (parallelised screening) to patients (correlating with current clinical MRSI). Long term, LIFETIME will empower assessment of the benefits and constraints of OoC technology in cancer and other aggressive disease research."